MassIVE MSV000093532

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Broad-specificity enzymes enable fast and cost-effective digestion for in-depth proteomics and precise label free quantitation

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Description

We have devised fast and robust SP3- and STRAP-based protocols for the broad-specificity proteases subtilisin, proteinase K, and thermolysin. All three enzymes are remarkably fast, producing near-complete digests in 1-5 min, and cost 200-1000x less than proteomics-grade trypsin. Using FragPipe resolved a major challenge by drastically reducing the duration of the required "unspecific" searches. In-depth analyses of proteinase K, subtilisin, thermolysin Jurkat digests identified 7374, 8178, 8752 unique proteins with average sequence coverages of 21%, 29%, 37%, including tens of thousands of amino acids not reported in the PeptideAtlas database spanning over 2400 experiments. While we could not identify distinct cleavage patterns, machine learning could distinguish true protease products from random cleavages, potentially enabling the prediction of cleavage products. 2D runs: 20 high-pH RP-HPLC fractions analyzed by DDA LC-MS/MS mode on a timsTOF Pro2, with Evosep; 15 SPD method, 200 ng peptide loaded on-column. STRAP vs SP3: each digest prepared in triplicate with SP3 and STRAP, respectiveyl-- analyzed by DDA nano-LC-MS/MS on an Orbitrap Exploris 480, 87 min gradient, 750 ng peptide loaded on-column. [doi:10.25345/C5QZ22T7D] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: machine learning ; label free quantitation ; high speed ; alternate broad proteases

Contact

Principal Investigators:
(in alphabetical order) 		Rene Zahedi, University of Manitoba, Canada
Submitting User: vspicer1
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Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.